Psychiatry

Latest AI and machine learning research in psychiatry for healthcare professionals.

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Spectral and Temporal Feature Learning With Two-Stream Neural Networks for Mental Workload Assessment.

People's mental workload profoundly affects their work efficiency and health. Mental workload assess...

Towards interpretable machine learning models for diagnosis aid: A case study on attention deficit/hyperactivity disorder.

Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that has heavy cons...

Using Artificial Intelligence to Identify Factors Associated with Autism Spectrum Disorder in Adolescents with Cerebral Palsy.

Autism spectrum disorder (ASD) is common in adolescents with cerebral palsy (CP) and there is a lack...

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.

BACKGROUND: Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that mea...

Long-term results of monopolar versus bipolar radiofrequency ablation procedure for atrial fibrillation.

BACKGROUND: In this study, we aimed to evaluate the long-term outcomes of monopolar or bipolar radio...

Spiking Neural Network Modelling Approach Reveals How Mindfulness Training Rewires the Brain.

There has been substantial interest in Mindfulness Training (MT) to understand how it can benefit he...

Selection and Optimization of Temporal Spike Encoding Methods for Spiking Neural Networks.

Spiking neural networks (SNNs) receive trains of spiking events as inputs. In order to design effici...

Design feasibility of an automated, machine-learning based feedback system for motivational interviewing.

Direct observation of psychotherapy and providing performance-based feedback is the gold-standard ap...

Identifying as American Indian/Alaska Native in Urban Areas: Implications for Adolescent Behavioral Health and Well-Being.

American Indian and Alaska Native (AI/AN) youth exhibit multiple health disparities, including high ...

Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: a machine learning approach.

BACKGROUND: It is becoming increasingly clear that pathophysiological processes underlying psychiatr...

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to d...

Application of Single-Nucleotide Polymorphisms in the Diagnosis of Autism Spectrum Disorders: A Preliminary Study with Artificial Neural Networks.

Autism spectrum disorder (ASD) includes different neurodevelopmental disorders characterized by defi...

Relative importance of symptoms, cognition, and other multilevel variables for psychiatric disease classifications by machine learning.

This study used machine-learning algorithms to make unbiased estimates of the relative importance of...

Evaluating the evidence for biotypes of depression: Methodological replication and extension of.

BACKGROUND: Psychiatric disorders are highly heterogeneous, defined based on symptoms with little co...

Predicting personalized process-outcome associations in psychotherapy using machine learning approaches-A demonstration.

Personalized treatment methods have shown great promise in efficacy studies across many fields of m...

EEG characteristics of children with attention-deficit/hyperactivity disorder.

The electroencephalogram (EEG) is an informative neuroimaging tool for studying attention-deficit/hy...

Classifying major depression patients and healthy controls using EEG, eye tracking and galvanic skin response data.

OBJECTIVE: Major depression disorder (MDD) is one of the most prevalent mental disorders worldwide. ...

Telehealth in Mental Health Nursing Education: Health Care Simulation With Remote Presence Technology.

The feasibility of integrating remote presence technology within a simulation scenario for psychiatr...

Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia.

Machine learning (ML) is a growing field that provides tools for automatic pattern recognition. The ...

Considering patient safety in autonomous e-mental health systems - detecting risk situations and referring patients back to human care.

BACKGROUND: Digital health interventions can fill gaps in mental healthcare provision. However, auto...

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